Embodiments of the invention relate generally to hybrid and electric vehicles, and more specifically to a system and method for energy management and operation of hybrid and electric vehicles.
Hybrid electric vehicles combine an internal combustion engine and an electric motor that is typically powered by one or more electrical energy storage components. Such a combination may increase overall fuel efficiency by enabling the combustion engine and the electric motor to each operate in respective ranges of increased efficiency. Electric motors, for example, may be efficient at accelerating from a standing start, while combustion engines may be efficient during sustained periods of constant engine operation, such as in highway driving. Having an electric motor to boost initial acceleration allows combustion engines in hybrid vehicles to be smaller and more fuel efficient.
In many conventional hybrid vehicles, electric motors also enable the capture of braking energy by acting as generators and providing such captured braking energy to energy storage components (ESCs). ESCs such as batteries, ultracapacitors, or flywheels are used to capture energy present during braking or generation operations for reuse at a later time. These components also provide load-leveling functionality to reduce transient loading to the primary power-producing device in the system. Such installations generally operate with limited or no information about the environment or terrain and lack predictive capability to foresee upcoming events. This often results in sub-optimal usage of the ESCs that can shorten life because of unnecessary applied stresses. Often, ESCs are over-sized for the application to ensure that stress limits are not exceeded, which adds cost to the system. Because such vehicles typically operate without information regarding environment or terrain, in order to react to charging and discharging events, the state of charge of the ESC is typically maintained near the midpoint of the useable storage range of the ESC.
If the vehicle is traveling in a valley or along a high point in the local terrain, hybrid energy recovery may not be maximized. For example, if the vehicle were at a high point in the local terrain with the ESC state of charge at the midpoint, the impending downhill regenerative capture opportunity ceases when the battery reaches full state of charge, which may occur partway down the hill. Accordingly, the full downhill regenerative capture opportunity is stopped short. In addition, the battery will likely charge at 100% power, operate at the limits of stress, and create excessive heat and temperature rise. The converse is true for starting at a low point in the terrain where the hybrid assist is halted when the battery is exhausted of charge prior to reaching the summit.
Typically, during a trip along a route, a control scheme for the vehicle may be based on conventional parameters such as elevation, route, terrain, and other topographical information. Such a control scheme can result, as an example, in a battery reaching a full charge despite having additional regenerative energy available. In this example, after the battery reaches a full charge, some regenerative energy that could otherwise be captured is lost, and overall system efficiency is thus lower than it otherwise could have been. In another example of a conventional control scheme, peak power demands may cause a battery bank to be fully depleted, resulting in an overall decreased life expectancy. Future trips along the same route that are based on these conventional parameters may repeat the same inefficiencies and fail to learn from past or historical experience.
A control scheme could include this historical knowledge to optimize overall system efficiency while improving overall life expectancy for future trips along the route. This control scheme may include, for instance, reducing battery bank storage in order to take full advantage of available regenerative power, or it may include avoiding full battery depletion while traveling along the route to reduce a deep draw on the battery that can reduce overall life of the battery. Such a control scheme may be based on historical knowledge that is input to a database and made available for future use. Thus, after one or more trips along the route, it is possible to adjust the operating or control parameters in order to learn from past experience and continually improve subsequent control schemes over the route. Each trip along the route thereby improves overall system performance, and as more data is accumulated of the route, peak overall performance can be achieved that is tailored to current operating conditions.
In order to enable later access to the historical data, the historical data is typically uploaded to a historical database. However, due to accuracy tolerances in Global Positioning System (GPS) sensors, GPS trajectories may not align with a road the vehicle is driving on. Thus, although useful information may be gained from a trip, such information may be lost due to an inability to match a location with links within a map, and thus it may not be properly associated with a known location in a map database. Further, conventional algorithms for determining a position within a map via a GPS sensor can be computationally intensive or burdensome. Thus, while useful data that includes position readings from a GPS sensor and associated power-use and other statistical information may be gained from a trip, the useful data may be lost in some instances when the algorithm for determining a vehicle location in a map database and uploading data to the historical database becomes overwhelmed and is unable to keep up with the realtime data acquisition rates.
It would therefore be desirable to have a system and method capable of efficiently creating a database and operation of a hybrid power system.